class_docstr: TorchRankerAgent implementation of the biencoder.
  
  It is a standalone Agent. It might be called by the Both Encoder.
code: def _set_text_vec(self, *args, **kwargs):
      obs = super()._set_text_vec(*args, **kwargs)
      # concatenate the [CLS] and [SEP] tokens
      if (
          obs is not None
          and "text_vec" in obs
          and "added_start_end_tokens" not in obs
      ):
          obs.force_set(
              "text_vec",
              surround(obs["text_vec"], self.START_IDX, self.END_IDX),
          )
          obs["added_start_end_tokens"] = True
      return obs
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  from parlai.utils.torch import padded_3d
  from parlai.zoo.bert.build import download
  from parlai.utils.io import PathManager
  from .bert_dictionary import BertDictionaryAgent
  from .helpers import BertWrapper, BertModel, add_common_args, surround, MODEL_PATH
  import os
  import torch
  from tqdm import tqdm
label_desc: Use image node_id 8 for calling the BiEncoderRankerAgent obj's underlying member method code with example usage: obj._set_text_vec() and returns: obs